# Temporal patterns in insulin needs for Type 1 diabetes

arXiv: https://arxiv.org/abs/2211.07393 · HTML: https://mlsanity.com/paper/2211.07393/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
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- First posted on arXiv 14 Nov 2022.

## Abstract (arXiv)

Type 1 Diabetes (T1D) is a chronic condition where the body produces little or no insulin, a hormone required for the cells to use blood glucose (BG) for energy and to regulate BG levels in the body. Finding the right insulin dose and time remains a complex, challenging and as yet unsolved control task. In this study, we use the OpenAPS Data Commons dataset, which is an extensive dataset collected in real-life conditions, to discover temporal patterns in insulin need driven by well-known factors such as carbohydrates as well as potentially novel factors. We utilised various time series techniques to spot such patterns using matrix profile and multi-variate clustering. The better we understand T1D and the factors impacting insulin needs, the more we can contribute to building data-driven technology for T1D treatments.